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By Joe Arney

If you鈥檙e like most people, when you saw an update to the terms and conditions to use The New York Times鈥� website last week, you just accepted them and moved on.听

But there was something unusual in this particular update鈥攁 prohibition on artificial intelligence.听

鈥淎 lot of folks who are creating content鈥攔eporters and writers, but also artists and others鈥攁re discovering that their work is essential for these models to function,鈥� said Robin Burke, professor and chair of the information science department at CU Boulder鈥檚 College of Media, Communication and Information. 鈥淎nd yet there鈥檚 this business model for which this is the input, but there鈥檚 no compensation for it.鈥�

Generative A.I. platforms like ChatGPT create content based on user input. If you ask it to write a thank-you note to your grandmother for the sweater she knitted for your birthday, it draws upon all the text it has 鈥渞ead鈥� online and generates a fairly convincing note. But there is no recognition for the writers whose prose generated the source material that make the A.I.鈥檚 output possible.听

The Times鈥� action forbids A.I. systems from scraping its content to train machine learning systems. So far, it鈥檚 the most influential shot fired as A.I.鈥檚 perceived impact looms in newsrooms, creative fields and beyond. 听

鈥淭he first round with A.I. has kind of been a free ride, because nobody was paying attention to what they were doing,鈥� Burke said. 鈥淣ow, I think it makes sense that the organizations producing content are thinking, 鈥楧o I really agree with this as a usage of my work?鈥欌��

A unique perspective on news, A.I.

Burke has unique expertise in this arena. He鈥檚 the son of a newspaper publisher and a scholar who is part of a team that鈥檚 creating tools for the close study of news recommender systems and their impacts on users, including journalists and editors.听

The Times is facing the same challenges as other papers in this new chapter of the digital age. But with a very robust subscriber base and a global audience, it is not really in the same category of daily newspapers that have been constricted by technologies that have moved audiences online and siphoned away significant advertising revenue. It鈥檚 easy to read journalists鈥� concerns over A.I. as a chance to correct what the industry got wrong at the dawn of the internet鈥攚hen publishers made their news free to everyone online, counting on the new technology of digital advertising to pay the bills.听

鈥淚n the early days of the Internet, people had a lot of different crazy ideas,鈥� Burke said. 鈥淎nd certain models came out of that鈥攕ome thrived, some failed鈥攂ut as it relates to A.I., we鈥檙e not far enough along to understand who the winners are.鈥�

Need proof? A month before the Times changed its terms, The Associated Press signed a deal to allow ChatGPT to scrape its archive going back to 1985.

鈥淎P is a little different, in that their model is very different from the Times鈥攖hey get their money mostly from publishers for using their content,鈥� Burke said. 鈥淚t might also be the case that OpenAI saw the writing on the wall and looked to AP as a reliable source, especially in case other publishers start to lock them out.鈥�

It鈥檚 something Burke feels is worth watching as he continues his research, particularly as those smaller papers face the choice of whether to restrict access to their reporting or consider A.I.鈥檚 role in a newsroom. If you鈥檒l task A.I. with analyzing government records in search of scandal, it鈥檚 not a far leap to just ask an algorithm to write the story, leaving out human judgment altogether.听

鈥淧art of that recommendation equation is this question of credibility,鈥� Burke said. 鈥淪o when an article is recommended to you, what does the system need to do to ensure it鈥檚 credible鈥攅ven if I might prefer some version of the news that suits my ideal ideological inclinations better?

鈥淚t鈥檚 why I think it鈥檚 such an important research goal to explore more of this space.鈥澨�